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An Optimal Balanced Economic Growth and Abatement Pathway for China Under the Carbon Emissions Budget

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  • Yongbin Zhu
  • Zheng Wang

Abstract

Arguments over equity during abatement goal setting is the principal obstacle to climate mitigation cooperation, while allocating global emissions to each country as deduced from the climate objective according to certain equitable principles offers an effective alternative to ending this dispute. Such an alternative also endows each country with the freedom to determine and develop its own pathway under its emissions budget while ensuring that global climate targets are met. Within this context, this paper integrated economic growth theory with the optimal control model and simulated the optimal abatement pathway as well as the economic growth trajectory for China within the allocated emissions budget. The study found that research and development (R&D) investment is an effective way of improving energy efficiency. Our simulation showed that the R&D intensity of the gross domestic product (GDP) would see a slight decline for the inceptive period, followed by an aggressive rise to a relatively high level before decreasing again. Under the 450 ppm carbon concentration target, the R&D investment intensity would have to increase significantly beginning from 2014 because of the more stringent demands as compared to other less rigorous targets such as 500 ppm. The economy would continue to grow, although growth would occur less rapidly under rigorous targets: relative to 2007 levels, the GDP would grow by 11-fold and 15-fold under the 450 and 500 ppm scenarios, respectively. Before enforcement of an effective R&D investment, the carbon emissions would increase rapidly, while after enforcement, the speed of carbon emissions would slow down. Copyright Springer Science+Business Media New York 2014

Suggested Citation

  • Yongbin Zhu & Zheng Wang, 2014. "An Optimal Balanced Economic Growth and Abatement Pathway for China Under the Carbon Emissions Budget," Computational Economics, Springer;Society for Computational Economics, vol. 44(2), pages 253-268, August.
  • Handle: RePEc:kap:compec:v:44:y:2014:i:2:p:253-268
    DOI: 10.1007/s10614-013-9383-x
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